A cross-sectional surveillance on healthcare-associated infections in a trauma centre in Eastern Uttar Pradesh: Experience of a student researcher

T. Banerjee, Amartya Seth, Arghya Das, Ravindra Singh
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Abstract

Objectives: Surveillance of healthcare-associated infection (HAI) is extremely important for the implementation and monitoring of infection prevention and control (IPC) policies and practices in health-care organisations. This study led by a Phase 2 medical student researcher was performed to assess the burden of different HAIs in a type 1 trauma centre. Materials and Methods: A cross-sectional study was conducted on patients with a provisional diagnosis of HAI. Pretested and predesigned pro forma fulfilling the criteria for surveillance of HAIs from the Centers for Disease Control and Prevention-National Healthcare Safety Network was used to collect data. The microbiological culture reports were reviewed. The rates of different HAIs were calculated in Microsoft Excel 2010 based on standard definitions. Results: The rates of catheter-associated urinary tract infection and ventilator-associated event (VAE) were 1.19/1000 catheter days and 36.99/1000 ventilator days, respectively. The surgical site infection rate was 4.97/100 surgeries with the majority of infections noted after orthopaedic interventions. Conclusions: Among all HAIs, VAE rate, mostly due to Acinetobacter baumannii, was higher than the existing Indian estimate, requiring immediate attention on prevailing IPC practices. The involvement of medical student researchers could help in the generation of baseline data in resource-limited settings.
北方邦东部创伤中心医疗保健相关感染的横断面监测:一名学生研究员的经验
目标:卫生保健相关感染(HAI)的监测对于卫生保健组织感染预防和控制(IPC)政策和实践的实施和监测极其重要。本研究由一名二期医学院学生研究人员领导,目的是评估1型创伤中心不同HAIs的负担。材料与方法:对临时诊断为HAI的患者进行横断面研究。采用预先测试和预先设计的形式,满足疾病控制和预防中心-国家卫生保健安全网络监测HAIs的标准,以收集数据。回顾了微生物培养报告。根据标准定义,在Microsoft Excel 2010中计算不同HAIs的发生率。结果:导管相关尿路感染发生率为1.19/1000导管d,呼吸机相关事件发生率为36.99/1000呼吸机d。手术部位感染率为4.97/100例,以骨科干预后感染为主。结论:在所有HAIs中,主要由鲍曼不动杆菌引起的VAE率高于印度现有的估计,需要立即关注流行的IPC做法。医学生研究人员的参与有助于在资源有限的情况下生成基线数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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